The present embodiments relate to a tomography system and a method for generating a volume model of a body volume. The volume model can be used to generate, for example, a volume graphic of the body volume, that is to say for example of the interior of a patient's body. The volume model is formed on the basis of pixel values of a plurality of projections of the body volume, wherein the projections are generated on a projection surface from different projection angles. When computing the volume model from the projections, a motion performed by the body volume between the times of projection is compensated. The tomography system according to one embodiment may be designed, for example, as an X-ray-based computed tomography scanner.
In order to generate each projection, radiation, for example X-rays, is projected through the body volume, that is to say for example the patient, onto radiation sensors of a detector in the form of beam bundles. The totality of the beams typically defines a beam fan (e.g., conventional computed tomography (CT)) or a cone beam (cone beam CT). The projection surface in total is provided by the totality of the radiation sensors, that is to say the matrix of the radiation sensors. Each radiation sensor generates a pixel value. Each pixel thus represents an individual surface element of the projection surface. By rotating the radiation source and the detector with its projection surface, the body volume is transilluminated from different projection angles.
The computation of the volume model can be based on the reconstruction of the beam profile of the beams, with which the body volume is transilluminated. As known from computed tomography: at a specific projection angle, the beam profile is reconstructed starting from the position of each radiation sensor up to the radiation source.
By reconstructing the beam profiles for all pixel values of the projections and for all projection angles, the result for individual volume elements of the body volume is a value, for example, of the absorption property of the material located in the volume element with respect to the radiation used. Such a value that is associated with a volume element is also referred to as a voxel value (voxel−volume element). A suitable indicated value for absorption coefficients are Hounsfield units (HU). The collection of the volume elements and of the voxel values ascertained in relation thereto form the described digital volume model, which can be provided as a so-called 3D image data set. In humans or animals, the position and form of tissue, bones and organs can be deduced in a volume model.
In order to obtain projections from different projection angles, the detector and the radiation source are moved around the body volume along a prespecified trajectory. Typically, a rotational movement about a rotation center in which the body volume is arranged is performed. The trajectory can thus be a circular orbit or a helix. Here, the detector generally does not follow the planned trajectory exactly. Owing to deformations of the carrier structure of the detector, due to weight, it is possible for the sensor position of each radiation sensor to deviate. This deviation of the sensor position should be taken into account when reconstructing the beam profile, so that the correct pixel values are combined with one another when it comes to computing the absorption coefficients of a specific volume element.
To this end, the deviations of the actual trajectory of the detector and of the radiation source from the planned trajectory can be described as the relative movement between the focus (radiation source) and the detector, and it is possible correspondingly to define detector position vectors U and V as a description of the position of the projection plane in space and a source vector S for the position of the focus. For each projection angle, such vectors U, V, S are defined in order to correct the sensor position or the source position in the reconstructions of the beam profiles (i.e. match them to real situations). If the movement of the body volume is still detected in that case, for example by filming a patient in a computed tomography scanner with a camera and thus deriving his or her movement, it is possible to determine another object vector O for each projection angle in order to compensate also for this movement of the body volume in the reconstruction. In other words, it is possible to specify for each projection angle a perspective transformation matrix of 3×4 elements, which can be used as the basis for the reconstruction of a beam profile.
It is possible to indicate by the detector position vectors U, V how the detector is displaced relative to the constructively envisaged position of the detector, for example owing to the deformations of the carrier structure, once the detector has assumed a specific projection angle. It is likewise possible by way of the source vector S to describe the displacement of the radiation source relative to the constructively envisaged position of the source. The respective constructively envisaged position is obtained from the type of construction of the mechanical suspension of the detector with the radiation sensors and of the radiation source, that is to say for example from the design plan. By way of example, the detector position vectors U, V and the source vector S can indicate that the detector is lower by one millimeter and the radiation source is tilted forward, for example by half a millimeter, in each case relative to the position that the detector and the radiation source would have in the case of an ideally rigid mechanical suspension.
So as to ascertain for each projection angle, the relative positional change of the detector (detector position vectors U, V) and of the radiation source (source vector S) with respect to one another, an off-line calibration measure can be used in which a phantom with a known geometry is recorded. However, special algorithms can also be used that can determine the geometry generally on the basis of image data of a patient (Y. Kyriakou et al., “Simultaneous misalignment correction for approximate circular cone-beam computed tomography,” in: Physics in Medicine and Biology, 53, 6267, 2008). This algorithm, for example, is further developed in the embodiments.
A motion compensation can be carried out by the detector position vectors U, V, the object vector O and the source vector S. The motion correction has so far been rigid, that is to say only translational movements in one spatial direction by a corresponding displacement were compensated for by the stated correction vectors (i.e., factored out). This applies both to the object movement and to a displacement of the detector relative to the radiation source. The object is here considered as an ideally rigid body which does not deform during movement. On the basis of this assumption, all parts of the object always carry out a movement in the same direction.
What is not possible in the prior art is the compensation of flexible, non-rigid movements, that is to say deformations, of a body volume. However, these can be caused for example by breathing movements of a patient. Such non-rigid movements prevent a consistent image reconstruction.